Data Labeling

Data labeling is the process of tagging data to train machine learning models. We review a range of data labeling tools and services, from audio annotation to image classification, to support AI development.

Top 20 Data Labeling Tools

Data LabelingSep 3

Data labeling, the process of annotating raw data (such as images, text or audio), is essential for training ML models to perform tasks like classification and recognition. Here, we introduce top 20 data labeling tools. The top data labeling tools: Ranking: From most to least comprehensive.

Data LabelingAug 25

Data Labeling for NLP with Real-life Examples

NLP technology is increasingly being used to enable smart communication between people and their devices. Companies like Google, Amazon, and OpenAI have invested billions in NLP technologies that can understand, interpret, and generate human language with remarkable accuracy. However, behind every sophisticated NLP model lies an important foundation: labeled training data.

Data LabelingJul 3

Audio Annotation

A subset of data annotation, audio annotation, is a critical technique for building well-performing natural language processing (NLP) models. These models offer numerous benefits to organizations, including analyzing text, speeding up customer responses, and recognizing human emotions. In this article, we take a deep dive into audio annotation to understand its importance for businesses.

Data LabelingJun 24

Intent Classification: What it is & How it Works

Customers have more options than ever due to increasing competition and the quality of customer service has become one of the key factors for businesses to stay ahead of the competition. This article, we will explore one of the techniques used in these applications: intent classification.

Data LabelingJun 16

10 Open Source Data Labeling Platforms

Data labeling, the process of annotating raw data (such as images, text, or audio), is essential for training ML models to perform tasks like classification and recognition. While pre-built solutions exist, they may not always meet specific needs, making open-source platforms a more flexible and customizable alternative. See the top 10 open-source data labeling tools.

Data LabelingJun 12

Human Annotated Data

As the AI market grows (Figure 1), integrating AI solutions remains challenging due to time-consuming tasks like data collection and annotation. Many use automated annotation tools to streamline the tedious process of data annotation, but robust machine learning models still require human-in-the-loop approaches and human-annotated data.

Data LabelingMar 19

Image Classification: 6 Applications & 4 Best Practices

Around 1.72 trillion1 photos are taken every year. Many are used to train digital solutions, such as self-driving systems powered by image recognition and computer vision (CV) technologies.